Title, Date of Publication & Journal

‘Climate warming will not decrease winter mortality’ by Philip L. Staddon et al will be published in Nature Climate Change at 18:00 UK time on Sunday 23 February.

Claim supported by evidence?

The paper does not provide robust support for the claim that climate warming will not decrease winter mortality, because the statistical methods used mean that there could still be an effect of cold temperature on number of deaths that is masked by an effect of influenza.  There are other limitations (see below).

Summary

• The study investigated the relationship between cold temperatures and excess winter deaths (EWDs).
• The authors conclude that cold temperatures were previously associated with EWDs (until the 1970s), but no longer are.
• The authors conclude that from the 1970s onwards, influenza has been the main factor associated with EWDs.
• Flaws in the statistical analysis mean that their conclusions may not be reliable because:
• Influenza and cold temperatures may not be independent of one another (if cold temperatures leave people more vulnerable to infections then cold may still affect EWDs via its effect on influenza).
• The statistical models the authors used contained both number of cold days (<5˚C) and number of days with a big temperature drop – these two measures are likely to be highly correlated with each other (we call this over-adjustment of the regression analysis).  The result is that there may actually be effects on EWDs of either cold days or days with a big temperature drop, but by including them both in the model their effects could be masked by one another.  Hence, there may still be an effect of cold temperature on EWDs beyond the 1970s but we are not seeing the effect because of the model used.
• The group of people looked at in this study is the over 65s.  Comparing those aged over 65 in the 1950s with those aged over 65 now may not be without problems because today there are many more people in this age group than there were in the 1950s, and because health improvements mean that many people aged 65 are healthier now than they were in the 1950s.

Study Conclusions

The authors report that there was previously a clear relationship between the number of cold winter days (defined as days with a temperature < 5°C) and EWDs, but that that relationship no longer holds.  The authors suggest that this is because improvements in healthcare and housing over recent decades have made people less vulnerable to the effects of cold.

This explanation seems plausible but the statistical analyses are not robust enough to conclude this for definite (see limitations section).

The conclusions that CAN be drawn are:

• There has been a substantial decrease in RATE of EWDs over the last six decades, but because authors do not report the absolute numbers of EWDs (rather they report the number as a proportion of the population of over 65s – the rate) we can’t tell whether there are now fewer EWDs or whether the population of over 65s has increased in size so there are PROPORTIONALLY fewer EWDs.
• Cold temperatures certainly were associated with EWDs until the 1970s.
• Since the 1970s influenza incidence has been strongly associated with EWDs.

Strengths/Limitations

Strengths:

• The study used data from a period of over 60 years – lots of data.
• The authors used a reliable source for the measurements of temperature (data from the UK’s Meteorological Office Hadley Centre).
• The authors used a reliable source of death data (data from the Office for National Statistics).

Limitations:

• The conclusion that there is no relationship between cold temperatures and EWDs in recent years may not be sound, because:
  1. The model contains both cold days and influenza incidence.  These two factors may not be independent – If increased influenza activity is affected by cold weather, then this adjustment is inappropriate, as cold temperature could affect EWDs via its effect on influenza activity. The paper does not present data on the correlation between cold temperatures and flu activity, so it is not possible to know how serious a problem this is from the paper.
  2. The model contained both number of days <5˚C and number of days with a big temperature drop – these two measures are likely to be highly correlated so although neither appear to be associated with EWDs this may be because each one is masking the other’s effect.  A model containing only one or the other measure of cold days may reveal a significant association with EWDs, but such a model has not been presented in this paper.
  3. The authors do not report the absolute numbers of EWDs – rather they report the number of EWDs as a proportion of the total population of over 65s (the rate of EWDs).  While results do suggest a substantial decrease in the rate of EWDs over the last six decades, it is possible that there is little change in the absolute number of EWDs if the population of over 65s has grown substantially.  Therefore, we don’t really know if the reduction in rate of EWDs is due to a decrease in absolute numbers of EWDs or due to an increase in the size of the population of over 65s.
  4. The dataset used a single geographic measure of temperature – that for central England. It is possible that this may have masked important regional temperature variations.  The measure of numbers of deaths was also a general population measure – there may be regional variations in this too.
  5. The authors chose to measure cold days as those <5˚C.  Other definitions of cold temperature could have been looked at too, such as mean temperature over the whole winter, minimum winter temperature, etc.
  6. It is not clear whether the time periods they looked at separately were decided in advance or once the data had been looked at – if it is the latter then results are less robust.
  7. EWDs are measured in the over 65s.  this was designed to account for demographic changes but may in fact introduce bias – the population of over 65s is not only much larger than in the 1950s but also healthier so may not all be at great risk of EWDs.

Glossary

EWDs = excess winter deaths